base_network.py 文件源码

def hidden_layers_on(self, layer, layer_sizes):
    if not isinstance(layer_sizes, list):
      layer_sizes = map(int, layer_sizes.split(","))
    assert len(layer_sizes) > 0
    for i, size in enumerate(layer_sizes):
      layer = slim.fully_connected(scope="h%d" % i,
                                  inputs=layer,
                                  num_outputs=size,
                                  weights_regularizer=tf.contrib.layers.l2_regularizer(0.01),
                                  activation_fn=tf.nn.relu)
#      if opts.use_dropout:
#        layer = slim.dropout(layer, is_training=IS_TRAINING, scope="do%d" % i)
    return layer